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[📑 Docs](https://docs.rig.rs)
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[🌐 Website](https://rig.rs)
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<a href="https://ryzome.ai"><img src="img/ryzome-bg.png" height="32" align="absmiddle" alt="Ryzome" /></a>

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✨ If you would like to help spread the word about Rig, please consider starring the repo!

> [!WARNING]
> Here be dragons! As we plan to ship a torrent of features in the following months, future updates **will** contain **breaking changes**. With Rig evolving, we'll annotate changes and highlight migration paths as we encounter them.

## Table of contents

- [Table of contents](#table-of-contents)
- [What is Rig?](#what-is-rig)
- [Features](#features)
- [Who's using Rig?](#who-is-using-rig)
- [Get Started](#get-started)
  - [Simple example](#simple-example)
- [Integrations](#supported-integrations)

## What is Rig?
Rig is a Rust library for building scalable, modular, and ergonomic **LLM-powered** applications.

More information about this crate can be found in the [official](https://docs.rig.rs) and [crate](https://docs.rs/rig/latest/rig/) API reference documentation.

## Features
- Agentic workflows that can handle multi-turn streaming and prompting
- Full [GenAI Semantic Convention](https://opentelemetry.io/docs/specs/semconv/gen-ai/) compatibility
- 20+ model providers, all under one singular unified interface
- 10+ vector store integrations, all under one singular unified interface
- Full support for LLM completion and embedding workflows
- Support for transcription, audio generation and image generation model capabilities
- Integrate LLMs in your app with minimal boilerplate
- Full WASM compatibility (core library only)

## Who is using Rig?
Below is a non-exhaustive list of companies and people who are using Rig:
- [St Jude](https://www.stjude.org/) - Using Rig for a chatbot utility as part of [`proteinpaint`](https://github.com/stjude/proteinpaint), a genomics visualisation tool.
- [Coral Protocol](https://www.coralprotocol.org/) - Using Rig extensively, both internally as well as part of the [Coral Rust SDK.](https://github.com/Coral-Protocol/coral-rs)
- [VT Code](https://github.com/vinhnx/vtcode) - VT Code is a Rust-based terminal coding agent with semantic code intelligence via Tree-sitter and ast-grep. VT Code uses `rig` for simplifying LLM calls and implementing the model picker.
- [Con](https://github.com/nowledge-co/con) - Con is a GPU-accelerated terminal emulator with a built-in AI agent harness. It uses Rig as the provider abstraction layer for its integrated coding agents.
- [Dria](https://dria.co/) - a decentralised AI network. Currently using Rig as part of their [compute node.](https://github.com/firstbatchxyz/dkn-compute-node)
- [Nethermind](https://www.nethermind.io/) - Using Rig as part of their [Neural Interconnected Nodes Engine](https://github.com/NethermindEth/nine) framework.
- [Neon](https://neon.com) - Using Rig for their [app.build](https://github.com/neondatabase/appdotbuild-agent) V2 reboot in Rust.
- [Listen](https://github.com/piotrostr/listen) - A framework aiming to become the go-to framework for AI portfolio management agents. Powers [the Listen app.](https://app.listen-rs.com/)
- [Cairnify](https://cairnify.com/) - helps users find documents, links, and information instantly through an intelligent search bar. Rig provides the agentic foundation behind Cairnify’s AI search experience, enabling tool-calling, reasoning, and retrieval workflows.
- [Ryzome](https://ryzome.ai) - Ryzome is a visual AI workspace that lets you build interconnected canvases of thoughts, research, and AI agents to orchestrate complex knowledge work.
- [deepwiki-rs](https://github.com/sopaco/deepwiki-rs) - Turn code into clarity. Generate accurate technical docs and AI-ready context in minutes—perfectly structured for human teams and intelligent agents.
- [Cortex Memory](https://github.com/sopaco/cortex-mem) - The production-ready memory system for intelligent agents. A complete solution for memory management, from extraction and vector search to automated optimization, with a REST API, MCP, CLI, and insights dashboard out-of-the-box.
- [Ironclaw](https://github.com/nearai/ironclaw) - A secure personal AI assistant
- [ilert](https://www.ilert.com/) - Incident management & alerting platform. Uses Rig as the multi-provider abstraction in its agentic LLM proxy powering ilert AI.

For a curated list of Rig projects, libraries, tools, articles, and production users, check out [awesome-rig](https://github.com/0xPlaygrounds/awesome-rig).

Are you also using Rig? [Open an issue](https://www.github.com/0xPlaygrounds/rig/issues) to have your name added!

## Get Started
Use the root `rig` facade when you want feature-gated access to companion crates,
or use `rig-core` directly when you only need the core provider abstractions.

```bash
cargo add rig
# or: cargo add rig-core
```

### Simple example
```rust
use rig::client::{CompletionClient, ProviderClient};
use rig::completion::Prompt;
use rig::providers::openai;

#[tokio::main]
async fn main() -> Result<(), anyhow::Error> {
    // Create OpenAI client
    let client = openai::Client::from_env()?;

    // Create agent with a single context prompt
    let comedian_agent = client
        .agent(openai::GPT_5_2)
        .preamble("You are a comedian here to entertain the user using humour and jokes.")
        .build();

    // Prompt the agent and print the response
    let response = comedian_agent.prompt("Entertain me!").await?;

    println!("{response}");

    Ok(())
}
```
Note using `#[tokio::main]` requires you enable tokio's `macros` and `rt-multi-thread` features
or just `full` to enable all features (`cargo add tokio --features macros,rt-multi-thread`).

You can find more examples in each crate's `examples` directory (for example, [`examples`](./examples)). Provider-specific integration coverage lives under [`tests/providers`](./tests/providers), with cassette-backed tests that replay offline by default and live-only tests kept separate when real provider APIs are still required. See [`tests/README.md`](./tests/README.md) for test target, replay, record, and cassette safety commands. More detailed use case walkthroughs are regularly published on our [Dev.to Blog](https://dev.to/0thtachi) and added to Rig's official documentation at [docs.rig.rs](https://docs.rig.rs).

## Supported Integrations

The root `rig` facade exposes companion crates behind one feature per integration:

```toml
rig = { version = "0.36.0", features = ["lancedb", "fastembed"] }
```

| Integration | Crate | Feature | Module path |
| --- | --- | --- | --- |
| AWS Bedrock | [`rig-bedrock`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-bedrock) | `bedrock` | `rig::bedrock` |
| AWS S3Vectors | [`rig-s3vectors`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-s3vectors) | `s3vectors` | `rig::s3vectors` |
| Cloudflare Vectorize | [`rig-vectorize`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-vectorize) | `vectorize` | `rig::vectorize` |
| FastEmbed | [`rig-fastembed`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-fastembed) | `fastembed` | `rig::fastembed` |
| Google Gemini gRPC | [`rig-gemini-grpc`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-gemini-grpc) | `gemini-grpc` | `rig::gemini_grpc` |
| Google Vertex AI | [`rig-vertexai`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-vertexai) | `vertexai` | `rig::vertexai` |
| HelixDB | [`rig-helixdb`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-helixdb) | `helixdb` | `rig::helixdb` |
| LanceDB | [`rig-lancedb`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-lancedb) | `lancedb` | `rig::lancedb` |
| Memory policies | [`rig-memory`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-memory) | `memory` | `rig::memory` |
| Milvus | [`rig-milvus`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-milvus) | `milvus` | `rig::milvus` |
| MongoDB | [`rig-mongodb`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-mongodb) | `mongodb` | `rig::mongodb` |
| Neo4j | [`rig-neo4j`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-neo4j) | `neo4j` | `rig::neo4j` |
| PostgreSQL | [`rig-postgres`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-postgres) | `postgres` | `rig::postgres` |
| Qdrant | [`rig-qdrant`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-qdrant) | `qdrant` | `rig::qdrant` |
| ScyllaDB | [`rig-scylladb`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-scylladb) | `scylladb` | `rig::scylladb` |
| SQLite | [`rig-sqlite`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-sqlite) | `sqlite` | `rig::sqlite` |
| SurrealDB | [`rig-surrealdb`](https://github.com/0xPlaygrounds/rig/tree/main/crates/rig-surrealdb) | `surrealdb` | `rig::surrealdb` |

`rig::memory` is available without the `memory` feature; it contains the core
conversation memory traits and in-memory backend re-exported from `rig-core`.
Enabling `features = ["memory"]` adds reusable history-shaping policy types from
the `rig-memory` companion crate to the same module.

We also have some other associated crates that have additional functionality you may find helpful when using Rig:
- `rig-onchain-kit` - the [Rig Onchain Kit.](https://github.com/0xPlaygrounds/rig-onchain-kit) Intended to make interactions between Solana/EVM and Rig much easier to implement.


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